Single-cell analysis in Python. Scales to >100M cells.
Annotated data.
An iterative multi-LLM consensus framework for accurate cell type annotation in single-cell RNA-seq data
An end-to-end Single-Cell Pipeline designed to facilitate comprehensive analysis and exploration of single-cell data.
muon is a multimodal omics Python framework
Enables cellxgene to generate violin, stacked violin, stacked bar, heatmap, volcano, embedding, dot, track, density, 2D density, sankey and dual-gene plot in high-resolution SVG/PNG format. It also performs differential gene expression analysis and provides a Command Line Interface (CLI) for advanced users to perform analysis using python and R.
Cell type annotation with local Large Language Models (LLMs) - Ensuring privacy and speed with extensive customized reports
Convert between AnnData and SingleCellExperiment
Learning cell communication from spatial graphs of cells
Bring your single-cell data to life
pseudobulking on an AnnData object
This repository extends scanpy to handle flow and mass cytometry data.
Notes and studies about single-cell RNA-Seq analysis
MiCV is a python dash-based web-application that enables researchers to upload raw scRNA-seq data and perform filtering, analysis, and manual annotation.
An easy-to-use PyTorch implementation of Automatic Cell-Types Identification of single-cell RNA sequencing using Neural Networks (ACTINN)
orthomap is a python package to extract orthologous maps (in other words the evolutionary age of a given orthologous group) from OrthoFinder/eggNOG results. Orthomap results (gene ages per orthogroup) can be further used to calculate weigthed expression data (transcriptome evolutionary index) from scRNA sequencing objects.
Sobolev alignment of deep probabilistic models for comparing single cell profiles
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